where \({\bf H}\in {\mathbb {R}^{m \times n}}\)  is the Jacobian of the function \(F\)  at a given operating point and is determined by the parameters and topology of the system. The vector of measurements \(Y^m\)  is corrupted by additive white Gaussian noise introduced by the sensors [1]}, [2]}. The noise vector \(Z^m\)  follows a multivariate Gaussian distribution, that is,
\( Z^m \sim \mathcal {N}(\textbf {0},\sigma ^2 \textrm {\textbf {I}}_m),\) 
